What Data Looks Like for This Product Category
The quality-related data for complete household appliance manufacturing covers the entire lifecycle of individual products. This includes configured BOMs, assembly work instructions, refrigerant charging records, electrical safety test reports, performance sampling inspection results, and rework records. Data is sourced from ERP/MES systems, component batch ledgers, tightening and charging device logs, safety compliance testers, performance laboratory data, and after-sales fault work orders. Update frequencies align with individual product output, shift-level summaries, and fixed sampling inspection cycles. Fields include batch numbers, process parameter values, test results, rework reasons, and no additional fictional statistical data.
Constraints on Tool Calling and Plugins
The high-frequency generation of single-unit level data requires tool calling to support low-latency batch requests, to avoid timeouts during individual calls. Heterogeneous data from multiple sources — device logs, process records, test reports, after-sales work orders — requires plugins to adapt to field parsing for different formats, and preset unified field mapping rules. In mixed-line assembly production scenarios, tool calling must associate with the corresponding model BOM for the current workstation, to avoid data confusion across product models. After-sales fault traceability requires plugins to link to component batch ledgers, and support quick retrieval of full-link associated data by product serial number.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Automatically match the tools required for the current quality traceability task, no manual specification of each call needed |
| Workflow/API function-call configuration | Enabled | Force the model to generate format-compliant tool call requests, adapting to multi-plugin linkage scenarios |
| Plugin timeout period | 30–60 seconds | Covers typical time for device log retrieval and BOM searches, preventing call failures from slow individual device responses |
| Number of returns per tool call | Top 10 entries | Limits returned data volume to avoid context overload, while covering primary associated data for a single batch |
| Context window size | 8000–12000 token | Covers context length of multi-source data, preventing truncation of critical process or test information |
| Plugin field mapping rules | Calibrated based on actual measurements | Adapts to format differences across multi-source heterogeneous data for this product category, unifying field names and units |
This configuration is based on FastGPT v4.17.0.
Three Common Configuration Mistakes
- Symptom: When specifying a model using
toolChoice, tool call return results do not meet expectations, and accuracy is lower than other models at the same level. Cause: Tool call format adaptation for the corresponding model has not been configured, causing the model to fail to correctly parse fields returned by plugins. - Symptom: After configuring a global Number type counter plugin, the counter does not automatically increment by 1 when the AI responds, and the field remains at its initial value. Cause: The plugin's automatic execution switch has not been enabled, or the counter variable has not been bound to the tool call's post-execution flow.
- Symptom: When calling an image generation plugin, all parameters are configured correctly but no results are generated, and an empty response is returned. Cause: Path mapping for the corresponding model has not been added in the plugin configuration, or correct model weight and ratio parameters have not been set.
How to Confirm Configuration Is Complete
- Submit a simulated quality traceability request, and check whether tool calling automatically matches the corresponding business data plugins.
- View plugin execution logs, confirm all configured parameters have been correctly passed, with no missing values or format errors.
- Verify update logic for counters or status variables, confirm variable values change as expected after execution completes.
- Compare plugin return results with actual business data, confirm associated fields such as batch numbers and process parameters match correctly.
The values provided here are common starting points, and should be evaluated against the reader's own samples.